class_docstr: Add gaussian noise to the input. A random Signal to Noise Ratio (SNR) will be picked
  uniformly in the decibel scale. This aligns with human hearing, which is more
  logarithmic than linear.
code: def randomize_parameters(
      self, samples: NDArray[np.float32], sample_rate: int
  ):
      super().randomize_parameters(samples, sample_rate)
      if self.parameters["should_apply"]:
          # Pick SNR in decibel scale
          snr = random.uniform(self.min_snr_db, self.max_snr_db)
  
          clean_rms = calculate_rms(samples)
          noise_rms = calculate_desired_noise_rms(
              clean_rms=clean_rms, snr=snr
          )
  
          # In gaussian noise, the RMS gets roughly equal to the std
          self.parameters["noise_std"] = noise_rms
  
file_path: audiomentations/audiomentations/augmentations/add_gaussian_snr.py
imports: import random
  import warnings
  import numpy
  from numpy.typing import NDArray
  from audiomentations.core.transforms_interface import BaseWaveformTransform
  from audiomentations.core.utils import calculate_desired_noise_rms, calculate_rms
label_desc: Use image node_id 2 for calling the AddGaussianSNR obj's underlying member method code with example usage: obj.randomize_parameters(samples, sample_rate) without return types